U.S. patent number 10,942,270 [Application Number 14/909,132] was granted by the patent office on 2021-03-09 for real-time autonomous weather and space weather monitoring.
This patent grant is currently assigned to Atmospheric & Space Technology Research Associates LLC. The grantee listed for this patent is Atmospheric & Space Technology Research Associates LLC. Invention is credited to Syed Mohammed Irfan Azeem, Geoffrey Crowley, Adam Scott Reynolds.
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United States Patent |
10,942,270 |
Reynolds , et al. |
March 9, 2021 |
Real-time autonomous weather and space weather monitoring
Abstract
Aspects of the invention are directed towards a system and
method for calculating ionospheric scintillation includes
calculating a motion-corrected perturbation of a GNSS radio signal
received by a monitoring device deployed in an oceanic
environment.
Inventors: |
Reynolds; Adam Scott
(Broomfield, CO), Azeem; Syed Mohammed Irfan (Louisville,
CO), Crowley; Geoffrey (Lafayette, CO) |
Applicant: |
Name |
City |
State |
Country |
Type |
Atmospheric & Space Technology Research Associates LLC |
Boulder |
CO |
US |
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Assignee: |
Atmospheric & Space Technology
Research Associates LLC (Boulder, CO)
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Family
ID: |
1000005410117 |
Appl.
No.: |
14/909,132 |
Filed: |
August 1, 2014 |
PCT
Filed: |
August 01, 2014 |
PCT No.: |
PCT/US2014/049472 |
371(c)(1),(2),(4) Date: |
January 31, 2016 |
PCT
Pub. No.: |
WO2015/017824 |
PCT
Pub. Date: |
February 05, 2015 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20170322303 A1 |
Nov 9, 2017 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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61901426 |
Nov 7, 2013 |
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61861948 |
Aug 2, 2013 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01S
19/40 (20130101); G01S 19/43 (20130101); G01S
13/74 (20130101); G01S 19/14 (20130101); G01S
19/07 (20130101); G01S 19/47 (20130101); G01W
1/02 (20130101); G01S 13/955 (20130101) |
Current International
Class: |
G01S
19/14 (20100101); G01S 19/40 (20100101); G01S
19/07 (20100101); G01S 19/47 (20100101); G01S
19/43 (20100101); G01S 13/74 (20060101); G01S
13/95 (20060101); G01W 1/02 (20060101) |
Field of
Search: |
;702/3 |
References Cited
[Referenced By]
U.S. Patent Documents
Foreign Patent Documents
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WO 2015/017824 |
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Feb 2015 |
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WO |
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Other References
Carrano et al., Ionospheric Monitoring with SCINDA, 2007. cited by
examiner .
GPS Ionospheric Scintillation & TEC Monitor (User's Manual) , 6
pages, 2007. cited by examiner .
ASTRA, "Programmable Dual Frequency GPS Receiver for Monitoring
Space Weather Cases SM-211 GPS Receiver", Data sheet 2014, 2 pages.
cited by applicant .
International Search Report and the Written Opinion of the
international Searching Authority, or the Declaration for
International Application, PCT/US2014/049472, dated Jan. 29, 2015,
14 pages. cited by applicant .
International Preliminary Report on Patentability for International
Application, PCT/US2014/049472 dated Feb. 2, 2016, 11 pages. cited
by applicant .
Strus, et al., "Precise Point Positioning Method for a Static
Survey in a High Multipath Environment", ION GNSS 17th
international Technical Meeting of the Satellite Division, Sep.
21-24, 2004, 9 pages. cited by applicant .
Communication of the Extended European Search Report for European
Application No. 14832999.8, dated Aug. 16, 2017, 11 pages. cited by
applicant .
Van Dierendonck, et al. "Measuring Ionospheric Scintillation in the
Equatorial Region Over Africa, Including Measurements From SBAS
Geostationary Satellite Signals", GPS Silicon Valley and European
Space Agency/European Space Research and Technology Centre, 8
pages, 2001. cited by applicant .
Xu, et al., "An Analysis of Low-Latitude Ionospheric Scintillation
and Its Effects on Precise Point Positioning", Journal of Global
Positioning Systems, 2012, vol. 11, No. 1: 22-32; 11 pages. cited
by applicant.
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Primary Examiner: Toatley, Jr.; Gregory J
Assistant Examiner: Dinh; Lynda
Attorney, Agent or Firm: Aspire IP Hawranek; Scott. L.
Parent Case Text
CROSS REFERENCE TO RELATED APPLICATION
This application is a National Stage of International Application
No. PCT/US14/49472, filed Aug. 1, 2014, which claims the benefit of
U.S. Provisional Application No. 61/861,948, filed Aug. 2, 2013,
and claims the benefit of U.S. Provisional Application No.
61/901,426, filed Nov. 7, 2013, the contents of each of the
foregoing applications are fully incorporated by reference herein.
Claims
What is claimed is:
1. A method of calculating ionospheric scintillation, comprising:
receiving one or more radio signals with an antenna of a monitoring
device, wherein each of the one or more radio signals is received
from a corresponding orbital navigation satellite located beyond an
ionosphere, wherein the monitoring device is located near the
Earth's surface, and wherein the antenna is in motion and the
antenna motion includes one or more of a tilt motion, a yaw motion
and a roll motion which increases noise in a carrier to noise
density ratio (C/No) during antenna motion; calculating, using
computational equipment with a processor, a perturbation of the one
or more radio signals that is corrected of the noise by the antenna
motion, wherein the calculating the perturbation comprises:
calculating, using computational equipment with a processor, a
navigation solution from a high rate phase data of the one or more
radio signals in a window of time; calculating, using computational
equipment with a processor, a change of a distance between the
monitoring device and the orbital navigation satellite using the
navigation solution for each time in the window of time; and
calculating, using computational equipment with a processor, a
phase of the perturbation using the high rate phase measurement
adjusted by the change of distance; and providing the ionospheric
scintillation calculation including compensation to the antenna
motion of the monitoring device over a network accessible by a
user.
2. The method of claim 1, wherein the calculating the navigation
solution comprises: interpolating the high rate phase data of the
one or more radio signals in the window of time; calculating an
offset of the high rate phase data and adding the offset to the
high rate phase data as corrected high rate phase data; and
calculating a high rate position of the monitoring device using the
corrected high rate phase data.
3. The method of claim 1, wherein the calculating the change of the
distance comprises: calculating the distance between the monitoring
device and the orbital navigation satellite for each of the orbital
navigation satellites corresponding to each of the one or more
radio signals using the high rate navigation solution; and
converting the distance to the change of the distance by adjusting
the distance with a reference distance.
4. The method of claim 1, wherein the calculating the phase of the
perturbation comprises: converting the change of the distance to
units of cycles with reference to a wavelength of the one or more
radio signals; adjusting the high rate phase data with the
converted change of the distance as adjusted high rate phase data;
and calculating the phase of the perturbation using the adjusted
high rate phase data.
5. The method of claim 4, further comprising filtering the adjusted
high rate phase data with a high pass filter to remove a drift
motion of the monitoring device.
6. The method of claim 1, further comprising sending the
perturbation to a server through a network.
7. The method of claim 1, wherein the calculating the perturbation
comprises: calculating a tilt angle of the antenna relative to the
orbital navigation satellite; and calculating an amplitude of the
perturbation based on an adjustment of a gain of the antenna at the
tilt angle.
8. The method of claim 1, wherein the orbital navigation satellite
is one of a Global Positioning System (GPS), Global Navigation
Satellite System (GLONASS), Galileo system, Indian Regional
Navigation Satellite System (IRNASS), and BeiDou Navigation
Satellite System (BDS).
9. The method of claim 1, wherein the monitoring device is deployed
in an oceanic environment.
10. The method of claim 9, further comprising calculating a wave
height of the oceanic environment, comprising: calculating a high
rate position of the monitoring device in a window of time; and
detrending a height of the antenna to remove a low frequency motion
of the monitoring device.
11. A monitoring device for calculating ionospheric scintillation,
comprising: an antenna; a radio frequency front end (RFE) in
electrical communication with the antenna, wherein the antenna is
configured to be in motion and the antenna motion includes one or
more of a tilt motion, a yaw motion and a roll motion, wherein the
antenna is configured to receive one or more radio signals, each of
the one or more radio signals received from a corresponding orbital
navigation satellite located beyond an ionosphere; a digital signal
processor (DSP) in electrical communication with the RFE; a
computer in electrical communication with the DSP, wherein the DSP
is configured for calculating a perturbation of the one or more
radio signals that is corrected of increased noise caused by the
antenna motion, wherein the calculating comprises: calculating a
navigation solution comprising an x-axis location, a y-axis
location and a z-axis location from a high rate phase data of the
one or more radio signals in a window of time; calculating a change
of a distance between the monitoring device and the orbital
navigation satellite using the navigation solution for each time in
the window of time; and calculating a phase of the perturbation
using the high rate phase measurement adjusted by the change of
distance; and providing the ionospheric scintillation calculation
including compensation to the antenna motion over a network
acceptable by a user.
Description
BACKGROUND
Field of the Invention
This invention relates generally to autonomous weather monitoring
and specifically to apparatus, systems, and/or methods for
ionospheric monitoring, modeling, and estimation of the same.
Discussion of the Background
Ionospheric variability can have a significant impact on
operational capabilities in many areas, including communications,
navigation, and surveillance operations. As such, ionospheric
monitoring is important for the support of requirements for global
space weather impacts specification and forecasting.
A significant source of data for specification and forecasting of
ionospheric effects are Global Positioning System (GPS) ionospheric
total electronic content (TEC) and ionospheric scintillation.
Traditionally, ground-based ionospheric monitoring systems (e.g.,
ground-based dual frequency GPS instruments) are used for such
measurements.
However, one deficiency with the related art is that the
availability of such ground-based ionospheric monitoring systems is
extremely limited in certain environments (e.g., oceanic regions,
theaters/tactical environments and/or other locations). The lack of
data from oceanic regions and theater locations adversely impacts
the ability for accurate regional and global ionospheric
specification and scintillation forecasting. Traditional
ground-based ionospheric monitoring systems have not permitted
coverage of large ocean areas or on-demand theater coverage.
SUMMARY OF THE INVENTION
Therefore, there is a need for ionospheric monitors, systems, and
methods that address the above deficiencies and other problems in
the related art.
One advantage of the present invention is to provide a system,
e.g., a lightweight, low-power, and fully-autonomous ionospheric
monitoring system that is able to provide fully processed and
highly accurate ionospheric TEC and scintillation parameters in
near real-time over a low data-rate satellite link.
Another advantage of the present invention is to provide error
estimates for the ionospheric TEC and scintillation parameters and
receive health and/or status information.
Yet another advantage of the present invention is to provide remote
unattended operation over areas such as oceans (e.g., using buoys,
boats, or other crafts), unfriendly/underdeveloped land masses in
which low power and satellite communications are essential, or
warfighting theaters where the GPS ionospheric monitors might be
disposable.
The present disclosure can provide a number of advantages depending
on the particular aspect, embodiment, and/or configuration. These
and other advantages will be apparent from the disclosure.
Additional features and advantages may be learned by the practice
of the invention.
To achieve these and other advantages, as embodied and broadly
described, a method of calculating ionospheric scintillation
includes measuring one or more radio signals received by an antenna
of a monitoring device. Each radio signal from a corresponding
orbital navigation satellite is located beyond an ionosphere to the
monitoring device located near the Earth's surface. The method
further includes calculating a perturbation of the radio signal
that is corrected of motion of the monitoring device. The
calculating the perturbation includes calculating a navigation
solution from a high rate phase data of the radio signal in a
window of time, calculating a change of a distance between the
monitoring device and the orbital navigation satellite using the
navigation solution for each time in the window of time, and
calculating a phase of the perturbation using the high rate phase
measurement adjusted by the change of distance. The calculating the
navigation solution includes interpolating the high rate phase data
of the radio signal in the window of time, calculating an offset of
the high rate phase data and adding the offset to the high rate
phase data as corrected high rate phase data, and calculating a
high rate position of the monitoring device using the corrected
high rate phase data. The calculating the change of the distance
includes calculating the distance between the monitoring device and
the orbital navigation satellite for each of the orbital navigation
satellites corresponding to each radio signal using the high rate
navigation solution and converting the distance to the change of
the distance by adjusting the distance with a reference distance.
The calculating the phase of the perturbation includes converting
the change of the distance to units of cycles with reference to a
wavelength of the radio signal, adjusting the high rate phase data
with the converted change of the distance as adjusted high rate
phase data, and calculating the phase of the perturbation using the
adjusted high rate phase data. The method further includes
filtering the adjusted high rate phase data with a high pass filter
to remove a drift motion of the monitoring device.
In another aspect, the calculating the perturbation includes
calculating a tilt angle of the antenna relative to the orbital
navigation satellite and calculating an amplitude of the
perturbation based on an adjustment of a gain of the antenna at the
tilt angle. The calculating the tilt angle is based on a pitch
motion, a yaw motion, and a roll motion of the monitoring device
and a position of the orbital navigation satellite. The readings of
the pitch motion, the yaw motion, and the roll motion are provided
by an inertial measurement unit (IMU). The calculating the tilt
angle includes calculating, at a plurality of time, corresponding
positions of the monitoring device, correlating the positions of
the monitoring device with positions derived from a high rate phase
navigation solution of the monitoring device, and calculating the
positions of the orbital navigation satellite corresponding to the
high rate phase navigation solution correlated to the positions of
the monitoring device.
In another aspect, the monitoring device is deployed in an oceanic
environment. The method further includes calculating a wave height
of the oceanic environment, including calculating a high rate
position of the monitoring device in a window of time and
detrending a height of the antenna to remove a low frequency motion
of the monitoring device.
In yet another aspect, an apparatus for calculating ionospheric
scintillation includes an antenna configured to receive one or more
radio signal, each radio signal from a corresponding orbital
navigation satellite located beyond an ionosphere, a monitoring
device, including a radio frequency front end (RFE) coupled to the
antenna, a digital signal processor (DSP) coupled to the RFE, and a
computer coupled to the DSP configured for calculating a
perturbation of the radio signal that is corrected of motion of the
monitoring device. The calculating the perturbation includes
interpolating the high rate phase data of the radio signal in the
window of time, calculating an offset of the high rate phase data
and adding the offset to the high rate phase data as corrected high
rate phase data, calculating a high rate position of the monitoring
device using the corrected high rate phase data, calculating the
distance between the monitoring device and the orbital navigation
satellite for each of the orbital navigation satellites
corresponding to each radio signal using a high rate navigation
solution, converting the change of the distance to units of cycles
with reference to a wavelength of the radio signal, adjusting the
high rate phase data with the converted change of the distance as
adjusted high rate phase data, and calculating the phase of the
perturbation using the adjusted high rate phase data. The apparatus
further includes filtering the adjusted high rate phase data with a
high pass filter to remove a drift motion of the monitoring
device.
In yet another aspect, the apparatus further includes a support
module. The support module includes a communication modem
configured for communication with a network coupled to the
monitoring device, a power management module coupled with and
configured for supplying power to the communication modem and the
monitoring device, and a battery coupled to the power management
module. The apparatus further includes a power source coupled to
the power management module. The power source comprises one or more
of a solar cell, a wind turbine, and a wave generator.
In still yet another aspect, a monitoring device for calculating
ionospheric scintillation includes a radio frequency front end
(RFE) coupled to the antenna, a digital signal processor (DSP)
coupled to the RFE, and a computer coupled to the DSP configured
for calculating a perturbation of the radio signal that is
corrected of motion of the monitoring device.
In still another aspect, a method of calculating ionospheric
scintillation, includes receiving ionospheric scintillation data
from a plurality of monitoring devices through a network. The
monitoring devices are located at a plurality of locations near the
Earth's surface. The method further includes aggregating the
ionospheric scintillation data from the plurality of monitoring
devices. The monitoring device is configured for receiving one or
more radio signals, each radio signal from a corresponding orbital
navigation satellite located beyond an ionosphere. The method
further includes calculating a perturbation of the radio signal
that is corrected of motion of the monitoring device. The
monitoring devices is further configured for the calculating the
perturbation of the radio signal that is corrected of motion of the
monitoring device. The method further includes calculating an
ionosphere weather model using the aggregated ionospheric
scintillation data and calculating a high frequency (HF)
propagation model using the ionosphere weather model. The method
further includes calculating a transmission frequency using the HF
propagation model for a location of a network device. The method
further includes storing the aggregated ionospheric scintillation
data as historical data. A network device has access to one or more
of the aggregated ionospheric scintillation data or calculations
using the aggregated ionospheric scintillation data based on a
subscription.
In still another aspect, a server includes an interface configured
for receiving ionospheric scintillation data from a plurality of
monitoring devices through a network. The monitoring devices are
located at a plurality of locations near the Earth's surface. The
service further includes a processor configured for aggregating the
ionospheric scintillation data from the plurality of monitoring
devices. The monitoring device is configured for receiving one or
more radio signals, each radio signal from a corresponding orbital
navigation satellite located beyond an ionosphere. The processor is
further configured for calculating a perturbation of the radio
signal that is corrected of motion of the monitoring device. The
processor is further configured for calculating an ionosphere
weather model using the aggregated ionospheric scintillation data
and calculating a high frequency (HF) propagation model using the
ionosphere weather model. The processor is further configured for
calculating a transmission frequency using the HF propagation model
for a location of a network device. The server further includes a
storage configured for storing the aggregated ionospheric
scintillation data as historical data. The server further includes
a storage configured for storing the aggregated ionospheric
scintillation data as historical data.
The phrases "at least one," "one or more," and "and/or" are
open-ended expressions that are both conjunctive and disjunctive in
operation. For example, each of the expressions "at least one of A,
B and C," "at least one of A, B, or C," "one or more of A, B, and
C," "one or more of A, B, or C" and "A, B, and/or C" means A alone,
B alone, C alone, A and B together, A and C together, B and C
together, or A, B and C together.
The term "a" or "an" entity refers to one or more of that entity.
As such, the terms "a" (or "an"), "one or more" and "at least one"
can be used interchangeably herein. It is also to be noted that the
terms "comprising," "including," and "having" can be used
interchangeably.
The term "automatic" and variations thereof, as used herein, refers
to any process or operation done without material human input when
the process or operation is performed. However, a process or
operation can be automatic, even though performance of the process
or operation uses material or immaterial human input, if the input
is received before performance of the process or operation. Human
input is deemed to be material if such input influences how the
process or operation will be performed. Human input that consents
to the performance of the process or operation is not deemed to be
"material."
The term "computer-readable medium," as used herein, refers to any
tangible storage and/or transmission medium that participate in
providing instructions to a processor for execution. Such a medium
may take many forms, including but not limited to, non-volatile
media, volatile media, and transmission media. Non-volatile media
includes, for example, NVRAM, or magnetic or optical disks.
Volatile media includes dynamic memory, such as main memory. Common
forms of computer-readable media include, for example, a floppy
disk, a flexible disk, hard disk, magnetic tape, or any other
magnetic medium, magneto-optical medium, a CD-ROM, any other
optical medium, punch cards, paper tape, any other physical medium
with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EPROM, a
solid state medium like a memory card, any other memory chip or
cartridge, a carrier wave as described hereinafter, or any other
medium from which a computer can read. A digital file attachment to
e-mail or other self-contained information archive or set of
archives is considered a distribution medium equivalent to a
tangible storage medium. When the computer-readable media is
configured as a database, it is to be understood that the database
may be any type of database, such as relational, hierarchical,
object-oriented, and/or the like. Accordingly, the disclosure is
considered to include a tangible storage medium or distribution
medium and prior art-recognized equivalents and successor media, in
which the software implementations of the present disclosure are
stored.
The term "module," as used herein, refers to any known or later
developed hardware, software, firmware, artificial intelligence,
fuzzy logic, or combination of hardware and software that is
capable of performing the functionality associated with that
element.
The terms "determine," "calculate," and "compute," and variations
thereof, as used herein, are used interchangeably and include any
type of methodology, process, mathematical operation or
technique.
It shall be understood that the term "means," as used herein, shall
be given its broadest possible interpretation in accordance with 35
U.S.C., Section 112(f). Accordingly, a claim incorporating the term
"means" shall cover all structures, materials, or acts set forth
herein, and all of the equivalents thereof. Further, the
structures, materials or acts and the equivalents thereof shall
include all those described in the summary of the invention, brief
description of the drawings, detailed description, abstract, and
claims themselves.
The preceding is a simplified summary of the disclosure to provide
an understanding of some aspects of the disclosure. This summary is
neither an extensive nor exhaustive overview of the disclosure and
its various aspects, embodiments, and/or configurations. It is
intended neither to identify key or critical elements of the
disclosure nor to delineate the scope of the disclosure but to
present selected concepts of the disclosure in a simplified form as
an introduction to the more detailed description presented below.
As will be appreciated, other aspects, embodiments, and/or
configurations of the disclosure are possible, utilizing, alone or
in combination, one or more of the features set forth above or
described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates an exemplary block diagram of a communication
network for a tracking system according to an embodiment;
FIG. 2 illustrates an exemplary block diagram of a monitoring
device according to an embodiment;
FIG. 3 illustrates an exemplary block diagram of a computer for a
monitoring device according to an embodiment;
FIG. 4 illustrates an exemplary block diagram of a support module
for a monitoring device according to an embodiment;
FIG. 5A-5C illustrate exemplary flow diagrams of a monitoring
process for a monitoring device according to an embodiment;
FIG. 6 illustrates an exemplary flow diagram of a .sigma..PHI.
calculation process for a monitoring device;
FIG. 7A-7C illustrate exemplary flow diagrams of a motion-corrected
.sigma..PHI. calculation process for a monitoring device according
to an embodiment;
FIG. 8 illustrates an exemplary flow diagram of a motion-corrected
.sigma..PHI. calculation process for a monitoring device according
to an embodiment;
FIG. 9 illustrates an exemplary flow diagram of a motion-corrected
S4 process for a monitoring device according to an embodiment;
FIG. 10A-10B illustrate exemplary flow diagrams of a wave height
calculation process for a monitoring device according to an
embodiment;
FIGS. 11A-11C illustrate exemplary PRNs according to an example of
the invention; and
FIGS. 12A-12E illustrate .sigma..PHI. measurements and calculations
for a test of a monitoring device according to an example of the
invention.
DETAILED DESCRIPTION
Embodiments herein presented are not exhaustive, and further
embodiments may be now known or later derived by one skilled in the
art.
Functional units described in this specification and figures may be
labeled as modules, or outputs in order to more particularly
emphasize their structural features. A module and/or output may be
implemented as hardware, e.g., comprising circuits, gate arrays,
off-the-shelf semiconductors such as logic chips, transistors, or
other discrete components. They may be fabricated with
Very-large-scale integration (VLSI) techniques. A module and/or
output may also be implemented in programmable hardware such as
field programmable gate arrays, programmable array logic,
programmable logic devices or the like. Modules may also be
implemented in software for execution by various types of
processors. In addition, the modules may be implemented as a
combination of hardware and software in one embodiment.
An identified module of programmable or executable code may, for
instance, include one or more physical or logical blocks of
computer instructions that may, for instance, be organized as an
object, procedure, or function. Components of a module need not
necessarily be physically located together but may include
disparate instructions stored in different locations which, when
joined logically together, include the module and achieve the
stated function for the module. The different locations may be
performed on a network, device, server, and combinations of one or
more of the same. A module and/or a program of executable code may
be a single instruction, or many instructions, and may even be
distributed over several different code segments, among different
programs, and across several memory devices. Similarly, data or
input for the execution of such modules may be identified and
illustrated herein as being an encoding of the modules, or being
within modules, and may be embodied in any suitable form and
organized within any suitable type of data structure.
In one embodiment, the system, components and/or modules discussed
herein may include one or more of the following: a server or other
computing system including a processor for processing digital data,
memory coupled to the processor for storing digital data, an input
digitizer coupled to the processor for inputting digital data, an
application program stored in one or more machine data memories and
accessible by the processor for directing processing of digital
data by the processor, a display device coupled to the processor
and memory for displaying information derived from digital data
processed by the processor, and a plurality of databases or data
management systems.
In one embodiment, functional block components, screen shots, user
interaction descriptions, optional selections, various processing
steps, and the like are implemented with the system. It should be
appreciated that such descriptions may be realized by any number of
hardware and/or software components configured to perform the
functions described. Accordingly, to implement such descriptions,
various integrated circuit components, e.g., memory elements,
processing elements, logic elements, look-up tables, input-output
devices, displays and the like may be used, which may carry out a
variety of functions under the control of one or more
microprocessors or other control devices.
In one embodiment, software elements may be implemented with any
programming, scripting language, and/or software development
environment, e.g., Fortran, C, C++, C#, COBOL, Apache Tomcat,
Spring Roo, Web Logic, Web Sphere, assembler, PERL, Visual Basic,
SQL, SQL Stored Procedures, AJAX, extensible markup language (XML),
Flex, Flash, Java, .Net and the like. Moreover, the various
functionality in the embodiments may be implemented with any
combination of data structures, objects, processes, routines or
other programming elements.
In one embodiment, any number of conventional techniques for data
transmission, signaling, data processing, network control, and the
like as one skilled in the art will understand may be used.
Further, detection or prevention of security issues using various
techniques known in the art, e.g., encryption, may be also be used
in embodiments of the invention. Additionally, many of the
functional units and/or modules, e.g., shown in the figures, may be
described as being "in communication" with other functional units
and/or modules. Being "in communication" refers to any manner
and/or way in which functional units and/or modules, such as, but
not limited to, input/output devices, computers, laptop computers,
PDAs, mobile devices, smart phones, modules, and other types of
hardware and/or software may be in communication with each other.
Some non-limiting examples include communicating, sending and/or
receiving data via a network, a wireless network, software,
instructions, circuitry, phone lines, Internet lines, fiber optic
lines, satellite signals, electric signals, electrical and magnetic
fields and/or pulses, and/or the like and combinations of the
same.
By way of example, communication among the users, subscribers
and/or server in accordance with embodiments of the invention may
be accomplished through any suitable communication channels, such
as, for example, a telephone network, an extranet, an intranet, the
Internet, cloud based communication, point of interaction devices
(point of sale device, personal digital assistant, cellular phone,
kiosk, and the like), online communications, off-line
communications, wireless communications, RF communications,
cellular communications, Wi-Fi communications, transponder
communications, local area network (LAN) communications, wide area
network (WAN) communications, networked or linked devices and/or
the like. Moreover, although embodiments of the invention may be
implemented with TCP/IP communications protocols, other techniques
of communication may also be implemented using IEEE protocols, IPX,
Appletalk, IP-6, NetBIOS, OSI or any number of existing or future
protocols. Specific information related to the protocols,
standards, and application software utilized in connection with the
Internet is generally known to those skilled in the art and, as
such, need not be detailed herein.
In embodiments of the invention, the system provides and/or
receives a communication or notification via the communication
system to or from an end user. The communication is typically sent
over a network, e.g., a communication network. The network may
utilize one or more of a plurality of wireless communication
standards, protocols or wireless interfaces (including LTE, CDMA,
WCDMA, TDMA, UMTS, GSM, GPRS, OFDMA, WiMAX, FLO TV, Mobile DTV,
WLAN, and Bluetooth technologies), and may be provided across
multiple wireless network service providers. The system may be used
with any mobile communication device service (e.g., texting, voice
calls, games, videos, Internet access, online books, etc.), SMS,
MMS, email, mobile, land phone, tablet, smartphone, television,
vibrotactile glove, voice carry over, video phone, pager, relay
service, teletypewriter, and/or GPS and combinations of the
same.
The ionosphere is a region of the Earth's upper atmosphere, ranging
from about 100 km to 800 km in altitude. The ionosphere is
distinguished by ionization of the atmospheric gases by solar and
cosmic radiation. The ionosphere is useful for high frequency (HF)
radio waves (e.g., shortwave radio at 1.6-30 MHz) communication
because the HF radio waves may be refracted by the ionosphere,
thereby extending the range of the communication by the HF radio
waves bouncing between the ionosphere and the Earth's surface. For
example, a transcontinental HF transmission may use several bounces
between the ionosphere and the Earth's surface.
Irregularities in the ionosphere affect the transmission of radio
waves as ionospheric scintillation. The effects include diffraction
and scattering of the radio signals and others as known in the art.
For HF radio waves refracted by the ionosphere, the practical
effect may be that the refracted radio waves may be bounced to a
different location from the intended receiver location. For
trans-ionospheric radio signals (e.g., signals from GPS satellites,
which may be at about 20,000 km orbits and have a frequency of over
1 GHz), the practical effect may be signal power fading, phase
cycle slips, receiver loss of lock, and degradation in the overall
quality of the received signal.
Ionospheric scintillation may be defined and measured as
perturbation in the phase and amplitude of the signals. The
.sigma..sub..PHI. may be measured as the root mean squared
perturbation of the phase. The S.sub.4 may be measured as the root
mean squared perturbation of the amplitude.
The ionospheric scintillation of a location in the ionosphere
varies over time depending on a number of factors that affects the
ionospheric weather (e.g., solar activity). The .sigma..sub..PHI.
and S.sub.4 may be measured on the Earth's surface through
measurement of data from GPS satellites (or other data). In an
embodiment, a model of the ionospheric weather and scintillation of
the ionosphere may be developed with enough readings of various
parts of the ionosphere using Earth-based monitoring systems
located at various points on the Earth's surface. In turn, this
ionospheric model may be used to develop an HF radio waves
propagation model for communication.
FIG. 1 illustrates an exemplary block diagram of a communication
network for a tracking system according to an embodiment.
Referring to FIG. 1, communication network 100 includes one or more
networks, including wide-area network 101, e.g., the Internet,
company or organization Intranet, and/or sections of the Internet
(e.g., virtual private networks, Clouds, and the Dark Web), and
local-area network 102, e.g., interconnected computers localized at
a geographical and/or organization location and ad-hoc networks
connected using various wired means, e.g., Ethernet, coaxial, fiber
optic, and other wired connections, and wireless means, e.g.,
Wi-Fi, Bluetooth, and other wireless connections. Communication
network 100 includes a number of network devices 110-115 that are
in communication with the other devices through the various
networks 101 and 102 and through other means, e.g., direct
connection through an input/output port of a network device 130,
direct connection through a wired or wireless means, and indirect
connection through an input-output box, e.g., a switch.
Network devices 110-115, which may also connect through the
networks 101 and 102 using various routers, access points, and
other means. For example, network device 113 wirelessly connects to
a base station 158, which acts as an access point to the wide area
network 101. Base station 158 may be a cellular phone tower, a
Wi-Fi router or access point, or other devices that allow a network
device, e.g., wireless network device 113, to connect to a network,
e.g., wide area network 101, through the base station 158. Base
station 158 may be connected directly to network 101 through a
wired or wireless connection or may be routed through additional
intermediate service providers or exchanges. Wireless device 113
connecting through base station 158 may also act as a mobile access
point in an ad-hoc or other wireless network, providing access for
network device 115 through network device 113 and base station 158
to network 101.
In some scenarios, there may be multiple base stations, each
connected to the network 101, within the range of network device
113. In addition, a network device, e.g., network device 113, may
be travelling and moving in and out of the range of each of the
multiple base stations. In such case, the base stations may perform
handoff procedures with the network device and other base stations
to ensure minimal interruption to the network device's connection
to network 101 when the network device is moved out of the range of
the handling base station. In performing the handoff procedure, the
network device and/or the multiple base stations may continuously
measure the signal strength of the network device with respect to
each base station and handing off the network device to another
base station with a high signal strength to the network device when
the signal strength of the handling base station is below a certain
threshold.
In another example, a network device, e.g., network device 115, may
wirelessly connect with an orbital satellite 152, e.g., when the
network device is outside of the range of terrestrial base
stations. The orbital satellite 152 may be wirelessly connected to
a terrestrial base station that provides access to network 101 as
known in the art.
In other cases, orbital satellite 152 or other satellites may
provide other functions such as global positioning and providing
the network device with location information or estimations of
location information of the network device directly without needing
to pass information to the network 101. The location information or
estimation of location information is known in the art. The network
device may also use geolocation methods, e.g., measuring and
analyzing signal strength, using the multiple base stations to
determine location without needing to pass information to the
network 101. In an embodiment, the global positioning functionality
of the orbital satellite 152 may use a separate interface than the
communication functionality of the orbital satellite 152 (e.g., the
global position functionality uses a separate interface, hardware,
software, or other components of the network device 113 than the
communication functionality). In another embodiment, the orbital
satellite with the global position functionality is a physically
separate satellite from the orbital satellite with communication
functionality.
In one scenario, network device, e.g., network device 112, may
connect to wide area network 101 through the local area network 102
and another network device, e.g., network device 110. Here, the
network device 110 may be a server, router, gateway, or other
devices that provide access to wide area network 101 for devices
connected with local area network 102.
FIG. 2 illustrates an exemplary block diagram of a monitoring
device according to an embodiment.
Referring to FIG. 2, the monitoring device is generally depicted as
reference 200. The monitoring device may be characterized as a
global navigation satellite system (GNSS) receiver for space
weather monitoring. In one embodiment, the signal is a GNSS signal.
Optionally, the GNSS receiver may be used as a GPS receiver. In one
embodiment, the signal is a GNSS signal. Optionally, the GNSS
receiver may be used as a GPS receiver. The monitoring device 200
includes a radio frequency front end (RFE) 220, digital signal
processor (DSP) 230, and computer 240 (e.g., single board computer
(SBC)). In an embodiment, the RFE 220 is configured to receive
signals from an antenna 290 (e.g., GPS antenna), where the antenna
is configured to receive signals from a corresponding satellite
(e.g., GPS satellite). For example, the RFE 220 may include an
intermediate frequency (IF) processor for managing and extracting
the data (e.g., GPS IF samples) from the antenna. The RFE 220 is in
electrical communication with the DSP 230, which may read the IF
samples from the RFE and track observables (e.g., pseudoranges such
as the distance between the GPS satellite and the antenna 290,
carrier phases, and Doppler measurements). The computer 240 is
coupled to the DSP 230, which may read the observables from the DSP
230, perform the adjustment calculations (e.g., scintillation
calculations), and store and/or send the data to the user.
In a preferred embodiment, the monitoring device 200 is implemented
with the various modules (e.g., RFE 220, DSP 230, and computer 240)
on one or more interface boards for reducing processing power
needs, e.g., with specialized hardware and instruction sets. In one
embodiment, the monitoring device 200 may include three boards
stacked vertically (with exemplary size of
4''.times.3.75''.times.1.25'' and weight of 200 g), a board for
each of the RFE 220, DSP 230, and computer 240. In an alternate
embodiment, the monitoring device 200 may be implemented as a
single device (e.g., the RFE 220, the DSP 230, the computer 240,
and also optionally the antenna 290 may be implemented as a single
device, such as using a general purpose computer or a virtual
machine using one instruction set). In another alternate
embodiment, the monitoring device 200 may be implemented over
multiple devices (e.g., multi-core devices or virtual devices). In
an embodiment, the monitoring device 200 or the various components
may be implemented through available components and devices as
known now or later derived in the art.
In an embodiment, the monitoring device 200 is configured to
perform one or more of the following obtain precise GPS total
electron content and scintillation, track through severe
scintillations, reliable operation in weak-signal environments,
flexible communication interfaces, remote
programming/reconfigurability, low unit cost makes it feasible to
deploy an array of receivers for more complete data acquisition,
available with or without WiFi capability, onboard computer reduces
infrastructure costs and complexity and includes optionally many
data recording solutions on board or off-board, e.g., storage
devices, network attached storage device, e.g., cloud storage,
combinations of the same and the like.
In an embodiment, the monitoring device 200 may be designed for
reduced power consumption configured for continuous or prolonged
operations through power generated in-situ with suitable modules,
e.g., solar panel power supply, wind power supply, wave power
supply, combinations of the same and the like, thereby allowing a
unit to be positioned a at a remote location without maintenance or
user intervention.
For example, the RFE 220 may include low power MMIC amplifiers and
power supply regulators. The RFE 220 may also include a current
monitor to the antenna port (for detecting the current from the
antenna 210) and an RF level monitor to the L1/L2 AGCs of the GPS
RFE for health monitor. Such health monitor modules may be part of
the data sent to the user via the network 100 as discussed with
respect to FIG. 1 and will be further discussed below. In one
implementation, the RFE 220 may be designed to operation with a
current of at least 275 mA and a voltage of at least 3.6 V.
In another embodiment, the monitoring device 200 may
optionally/alternatively include a location module configured for
geo-location of the monitoring device 200. The geo-location module
may include geo-location sensors as known in the art configured to
perform geo-location techniques for location of the module.
In another example, the computer 240 may be a single board
computer. The single board computer is designed with a physical
layout to match the profiles of RFE 220 and the DSP 230 and may be
manufactured using PCB manufacturing.
In embodiment, the DSP clock speed of the DSP 230 may be reduced to
at least 720 MHz or lower in order to reduce the power consumption
of DSP 230. In empirical testing, a DSP clock speed of 720 MHz
reduces DSP board power consumption by about eleven and half
percent (11.5%) over a DSP clock speed of 1.02 GHz while increasing
CPU (e.g., computer 240) utilization by about thirty five percent
(35%). The DSP 230 may also use a modified acquisition strategy
such as eliminating unnecessary computations that acquires even
non-existent signals. For example, an acquisition loop process of
the DSP 230 may cycle through all of the available pseudorandom
noise codes (PRNs) in the constellation at a rate of one per
second. After the initial navigation solution, the GPS almanac data
is used to calculate each PRNs azimuth and elevation. As such, this
process acquires non-existent signals at the expense of wasted
power. In an embodiment, the DSP 230 may acquire only the PRNs that
should be visible while ignoring the non-visible PRNs.
In an embodiment, the DSP 230 may use DSP protocols as known in the
art or may be later derived in the art. In a preferred embodiment,
the DSP 230 may use the multi-channel buffered serial port (McBSP)
protocol available on Gumstix devices (e.g., Gumstix SBC) to
facilitate bi-directional communication between the DSP 230 and the
computer 240. In a further embodiment, a serial protocol (e.g.
McBSP) may support at least 500 kbit/s bandwidth for data
transmission between the DSP 230 and the SBC 240.
In a preferred embodiment, the monitoring device 200 receives and
processes parameters including high rate data (per channel) at a
configurable rate of about 50-100 Hz, such as integrated carrier
phase, in-phase accumulation, quadrature accumulation, GPS time,
and receiver time, low rate data (per channel) at a configurable
rate of 1 Hz or greater, such as pseudorange-based TEC, phase-based
delta TEC, pseudorange, integrated carrier phase, GPS time,
receiver time, Doppler frequency, SV elevation, SV azimuth, C/N0,
data validity flag, cycle slip flag, signal acquisition status,
PRN, and SV health, scintillation parameters (per channel at a
configurable rate of about 0.01 Hz, such as S.sub.4,
.sigma..sub..PHI., .tau..sub.o, scintillation power ratio, GPS
time, reference channel status, PRN, and other parameters at a
configurable rate of 1 Hz or greater, such as receiver X/Y/Z
position, receiver X/Y/Z GPS time, receiver time, velocity,
receiver clock error, receiver clock error rate, and navigation
solution flag.
The monitoring device may include fixed or adjustable parameters.
The adjustable parameters may be configured through software
changes, which is an advantage over the related art. In an
embodiment, the parameters include one or more of a number of
tracking channels, low rate data cadence, Scintillation parameters,
high rate data availability & cadence, data storage options,
EML chip spacing, PLL loop order, PLL bandwidth, PLL discriminator
type, DLL bandwidth, FLL bandwidth, FLL weak bandwidth, Code
generation type, navigation smoothing parameters, SPR threshold for
non-scintillating channel, window length for scintillation,
calculations, frequency resolution for SPR calculation,
scintillation threshold for triggering, selective availability of
high rate data, elevation mask for scintillation triggering.
Optionally, the parameters are hardware configured or a combination
of hardware and software. In one embodiment, the channel
configuration is customizable, e.g., 40 channels to for signal
tracking, e.g., L1 and L2C. The data rate is configurable.
FIG. 3 illustrates an exemplary block diagram of a computer for a
monitoring device according to an embodiment.
The computer 300 may be a single board computer 240 as discussed
above with respect to FIG. 2. The computer 300 is configured
perform at least general purpose calculations (e.g., scintillation
calculation) and package, save, and/or send the calculated data to
a user.
Referring to FIG. 3, the computer 300 includes one or more
processors 322, storages 324, memories 326, and input and output
interfaces 328. A computer 300 may or may not contain all of the
above components depending on the purpose and use of the device.
For example, the computer 300 may be a dummy terminal that only
requires an input and output interface to send the input and
receive the output from a device that contains a processor for
processing the input and outputs.
The computer 300 may be connected with one or more displays 361,
peripheral devices 362, network interfaces 363, and input devices
364. Displays 361 may be visible screens, audible speakers,
holographic displays, Braille text devices, other devices, and
combinations of the same, that are configured to output information
to a user. Peripheral devices 362 may include printers, external
storages, other devices, and combinations of the same. Network
interfaces 363 may include wired and wireless interfaces that
connect the computer 300 to a network, other devices, and
combinations of the same. Input devices 364 may include keyboards,
mice, other input devices to input information to the computer 300,
and combinations of the same. The one or more devices may be
connected with or integral to the computer 300. For example, a
monitoring device 200 may have an integrated display 361 which may
pull up an input device 364, e.g., a soft keyboard, in a touch
screen of the display 361. Another device may have a separate
display monitor 361 connected to a display port, e.g., VGA, DVI,
HDMI, other standard, and/or combinations of the same, of the
computer 300 and a hardware keyboard connected to the device 310
through an input port, e.g., keyboard port and USB.
FIG. 4 illustrates an exemplary block diagram of a support module
for a monitoring device according to an embodiment.
In one embodiment, the monitoring device 200 may be used at remote
locations such as oceanic locations, e.g., positioned on buoys,
oceanic crafts, or other locations (e.g., tactical sites in hostile
or underdeveloped environment). For example, such locations may
lack power or communication infrastructures. As such, the
monitoring device 200 may require a standalone system supplying
power and communication, e.g., satellite communication, to the
network 100. In one embodiment, the satellite communication
includes, e.g., TDMA and/or DFMA using L-band spectrum as with the
Iridium system or others as known in the art.
Support module 400 includes a power management module 411 (e.g.,
power management computer and/or EPS), monitoring device 200,
battery 414, satellite modem or other communication device 413, and
corresponding antenna 412 for the satellite modem or other
communication device 413. The power management module 411 is
coupled to the battery 414 for supplying power to the monitoring
device 200 and the communication device 413, which is coupled to
the corresponding antenna 412. In an embodiment, the support module
400 may include the power management module 411 optionally, and the
battery 414 directly supplies power to the monitoring device 200
and the communication device 413. In another embodiment, the
support module 400 includes or is connected to a solar panel or
other power generator/source 490 (e.g., wind turbine) for producing
power to support module 400 and/or charging battery 414 (through
the power management module 411).
The communication device 413 may be a satellite modem (e.g.,
Iridium modem) configured for communication between the monitoring
device 200 with the network 100 (e.g., through satellite 152, such
as an Iridium satellite). The communication device 413 connects
with the monitoring device 200 through the computer 240 using a
serial data link.
In an embodiment, the support module 400 may include a packaging on
the outside of the support module 400 for providing weather
resistance, thermal management, and other outside element
management to the support module 400. The packaging may also be of
a suitable size, weight, and other properties for deployment at a
target location. For example, the packaging may be configured to
contain the support module 400 in a sealed environment inside the
packaging. The antenna 412 and the power source 490 (e.g., solar
panel) may be secured to the outside of the packaging. In a further
embodiment, the packaging may include or be placed on a buoy that
floats on water configured for an oceanic environment. The sealed
environment may include waterproof, weatherproof, hermetically
sealed and combinations of the same configured for the environment
and/or location. The environment may also be radiation hardened as
known in the art.
In a preferred embodiment, the support module 400 may include four
(4) solar panels, each dimensions approximately
505.times.352.times.28 mm and weighs 5 lbs (e.g., Everbright
03203). Each solar panel may produce a peak power of 25 W at an OC
voltage of 21.8 V and a SC current of 1.59 A. The DC converter or
regulator for the solar panels may produce an output of 5 V (e.g.,
as the operating voltage for the monitoring device 200). The
battery may have a voltage of about 12-14.8 V and capacity ranging
from 252-312 Wh. The battery may be dimensioned from
5''.times.3''.times.2.5'' to 7''.times.6.6''.times.7''.
FIG. 5A-5C illustrate exemplary flow diagrams of a monitoring
process for a monitoring device according to an embodiment.
Referring to FIG. 5A, the monitoring process starts with the GPS
antenna process 510. For example, the GPS antenna process 510 may
include the GPS antenna 290 receiving incoming data from the
corresponding GPS satellites.
Next, the RFE 220 conducts the RFE process 520. The RFE process 520
starts with step 521 to downconvert incoming data from the GPS
antenna 290 to an intermediate frequency (IF).
Next, the RFE 220 uses a high speed analog to digital converter
(A/D) to sample the IF data in step 522. In an embodiment, data
from the L.sub.1 and L.sub.2 band of the GPS frequency is used. The
high speed A/D may use about 2 MHz bandwidth per L.sub.1 and
L.sub.2 band for a total of 4 MHz. In an embodiment, a preferred
sample rate may be in the range of about 4 to about 40 MHz. This
corresponds to the use of a 40 MHz serial clock frequency and a 10
MHz oscillator. In a preferred embodiment, the sample rate is 40
MHz/7 or 5.7 MHz.
Next, in an embodiment, the top three (3) bits of the A/D output
are used to assign each sample of the IF data to a 2-bit magnitude
and sign in step 523. This step 523 helps reduce the processing
bitrate by the DSP. For example, the top bit of the three bit A/D
output may be the sign bit. According to an embodiment, a 2-bit
magnitude and sign may be assigned for each sample value of the
L.sub.1 and L.sub.2 band. As such, a 4-bit sample may be used, two
for each magnitude and sign of the L.sub.1 and L.sub.2 band
respectively. This requires 4-bit.times.5.7 MHz=22 Mbit/s bit rate
for sending to and processing by the DSP 230. In another
embodiment, the bit resolution of the output of the A/D may be set
according to other criteria.
The raw IF samples are sent to the DSP 230 for processing in step
524.
Referring to FIG. 5B, next, the DSP 230 conducts the DSP process
530. The DSP process 530 starts with step 531 to read the raw IF
samples from the RFE 510. In a preferred embodiment, the McBSP
protocol may be used for this step 531. In a further embodiment, a
serial protocol that supports at least bandwidth of the bit
resolution as assigned in step 522 may be used for the data
transmission in this step 531.
Next, the raw IF samples are used for the acquisition of the
location of the monitoring device 200 in step 532 and the tracking
of the monitoring device 200 in step 533. In an embodiment, this
acquisition process is fast Fourier transform (FFT) based. In a
preferred embodiment, the acquisition process in step 532 and the
tracking process in step 533 may be performed as disclosed in U.S.
Pat. Nos. 7,010,060 and 7,305,021, both of which are herein
incorporated by reference in their entireties.
Next, the high rate phase is calculated in step 534. For example,
the high rate phase may be in the range of 25 Hz up to 1 kHz,
typically from 50 to 100 Hz. The low rate phase may be derived from
the high rate phase and is on the order of about 0 Hz to about 25
Hz, typically at about 1 Hz.
Next, the high and low rate observables, such as the low rate
pseudorange, validity, and cycle slip flag are calculated in step
535. It is noted that these parameters consist the GPS observables.
In an embodiment, the low rate pseudorange, validity, and cycle
slip flag are of particular relevance to the calculation of the
.sigma..sub..PHI..
The high and low rate observables are sent to the computer 240 for
processing in step 536.
Referring to FIG. 5C, next, the computer 240 conducts the SBC
process 540. The SBC process 540 starts with step 541 to read the
high and low rate observables from the DSP 230.
The computer 240 may perform a scintillation calculation in step
542. In an embodiment, the scintillation calculation may include
compensation for monitoring devices that are deployed in an oceanic
environment that requires correction due to the effect of the
antenna motion. Further details on the scintillation calculation
will be discussed below with respect to FIGS. 6-10.
Next, all calculated data is packaged for the user in step 543. The
raw packaged data may be in the form of double precision float or
other suitable data type depending on the need for maximum
precision or with less precision to save memory. In step 543, the
calculated data may be packaged according to a desired output data
of the user. The packaged data is saved to a local disk (e.g.,
storage 324) and/or sent to the user through a local port (e.g.,
peripheral device 362) or through network 100 in step 544.
In an implementation, the monitoring device 200 may be implemented
as one or more of a discrete device, software as a service (SAAS)
module, an integrated solution device (e.g., a combination of the
monitoring device 200 and other related devices for providing an
integrated solution), and other devices. In one implementation, the
monitoring device 200 as an SAAS may need the data to be packaged
to be sent through a wired or wireless means to a centralized
server at a point of network 100, and the centralized server may
serve the data in packaged or other form as needed to the user
(e.g., to the user's mobile device). In another implementation, the
SAAS may send the packaged data in a form as needed directly to the
user's device through the wired or wireless means at a point of the
network 100. The user's device may include a control software able
to communicate with and/or code data from the monitoring device 200
using an API or other means as now known or later derived.
In another implementation, the monitoring process for the
monitoring device 200 may include a further step of receiving
instructions from a user through a wired or wireless means locally
or through a network 100 for making adjustments or corrections to
the monitoring device 200 such as making corrections to the GPS
antenna 290 or other corrections.
In an embodiment, a server or a collection point 110 at a network
101 may be used to receive and collect the data from various
monitoring devices 200 located at various locations. The server may
aggregate the data from the various monitoring devices 200 and
package the data to form an ionospheric weather report. In an
embodiment, ionospheric modeling and HF propagation modeling may be
performed to obtain the corresponding models to facilitate radio
communication. Such ionospheric model and HF propagation model may
be served to the various network devices 111-115 as an SAAS (e.g.,
through an application on the network devices 111-115) or through
other means (e.g., downloadable from the server 101, pushed to the
network devices 111-115, etc.). In another embodiment, the raw data
received and collected by the server 110 may be available to other
uses (e.g., the network devices 111-115 obtaining the raw data and
performing their own analysis on the data, a third-party obtaining
the raw data for record and storage, etc.).
In a further embodiment, historical data on ionospheric weather may
be collected and stored. This may be useful in a forensic context.
For example, an oceanic vessel, e.g., ship, may have lost contact,
but the ship's last known radio signal was known to have been
received by a receiver at a certain location at a certain time. The
historical data on the ionospheric weather may be used to determine
the ship's location at the time when the radio signal was sent by
backtracking from the known receiver's location. In another
embodiment, the historical data on the ionospheric weather may be
supplied to third parties for other analysis.
FIG. 6 illustrates an exemplary flow diagram of a .sigma..sub..PHI.
calculation process for a monitoring device.
In an application where the monitoring device 200 is deployed at a
static location, the .sigma..sub..PHI. for the monitoring device
200 may be calculated using the .sigma..sub..PHI. calculation
process 600.
The process 600 starts with step 610 to read 50-100 seconds window
of the high rate phase calculated by the DSP 230 (e.g., by step
534). Next, the .sigma..sub..PHI. is calculated using the high rate
phase in step 620. An exemplary calculation may include taking a
high pass of the high rate phase. The .sigma..sub..PHI. calculation
may also include any necessary clock correction as needed. Next,
the .sigma..sub..PHI. is normalized for each PRN for this window in
step 630. Example PRNs are illustrated in FIGS. 11A-11C.
FIG. 7A-7C illustrate exemplary flow diagrams of a motion-corrected
.sigma..sub..PHI. calculation process for a monitoring device
according to an embodiment.
In an application where a monitoring device is used in an oceanic
environment, the effect of the antenna motion due to the oceanic
environment needs to be accounted for versus a traditional
land-based monitoring device. The effect of antenna motion due to
the oceanic environment includes periodic oscillation in the
amplitude of the GPS signals being tracked (increased S.sub.4) as
the monitoring device pitches and rolls while riding the waves of
the oceanic environment. Also, the translational motion of the
antenna will advance and retard phase measurements (increased
.sigma..sub..PHI.). Such effects of the antenna motion on
.alpha..sub..PHI. and S.sub.4 may be processed using a multipath
mitigation algorithm.
The following settings for the processing algorithm performed by
the DSP 230 is recognized as preferable for computing the
motion-corrected .sigma..sub..PHI. in an empirical study as will be
discussed with respect to FIGS. 12A-12E: EML chip spacing of 0.1;
PLL bandwidth of 40 Hz, and DLL bandwidth of 0.05 Hz.
Motion-corrected .sigma..sub..PHI. calculation process 700 starts
with step 711 to read a 50-100 second window of high rate phase and
low rate (or high rate if available) pseudorange, and status flag.
Generally, scintillation may be calculated using windows of around
1 minute, hence the 50-100 second window.
Next, the phase, pseudorange, and status flag are interpolated onto
a common high rate timestamp in step 713. The interpolation may be
done using interpolation methods as known now or may be later
derived (e.g., linear or quadratic interpolation). As every PRN has
its own time series but with an offset of a certain time (e.g., on
the order of ms), the interpolation obtains further resolution of
the data on an integrated carrier phase. In an embodiment, a linear
interpolation may be computed at around 100 Hz, and quadratic
interpolation may be computed at around 25 Hz.
Next, the corresponding validity and cycle slip flags of the data
are used to assign a unique arc number to each continuous high rate
phase arc in step 715. In an embodiment, each PRN may correspond to
around 10 seconds worth of data for a usable arc data. Referring to
FIG. 11A, PRN 13 includes a complete arc 1 in a 100 seconds window.
Referring to FIG. 11B, PRN 17 includes an incomplete arc 2 of less
than 20 seconds of valid data because the signal was dropped.
Referring to FIG. 11C, PRN 20 includes an arc 3 for around 90
seconds and a slip at around the 90 seconds point before the data
continues with arc 4 after the slip.
Next, an approximately one (1) second decimated copy of all data is
made in step 717. In an embodiment step 717 may be optional and
helps speed up the calculation process depending on the application
(e.g., generally, the calculation requires no more than 1 s
resolution).
Next, the decimated pseudorange is used to calculate an approximate
receiver location in step 719. In an embodiment, a standard GPS
navigation solution may be used.
Next, the approximate receiver location is used to add ionospheric,
tropospheric, and relativistic corrections to the decimated phase
in step 721.
Next, the corrected decimated phase is used to solve the phase
ambiguity for each arc in step 723. In this step 723, the solution
may be derived using the process as disclosed in Joseph M. Strus,
et al., "Precise Point Positioning Method for a Static Survey in a
High Multipath Environment," ION GNSS 17th International Technical
Meeting of the Satellite Division, 21-24 Sep. 2004, p. 1856-63,
which is herein incorporated by reference in its entirety.
Next, any arcs that are not continuous for the entire time range
are filtered out in step 725. For example, non-continuous arcs may
include invalid arcs as illustrated in FIG. 11B and non-cycle slip
free arcs as illustrated in FIG. 11C.
Next, the calculated ambiguity is added into the high rate phase
for each arc in step 727. In an embodiment, the offset may be the
average or DC response of the high rate phase for a window.
Next, the receiver location is used to add ionospheric,
tropospheric, and relativistic corrections to the unambiguous high
rate phase in step 729. This step 729 is the same as step 721 but
applied to the high rate corrected phase data instead of the
decimated data. This step 729 is optional depending on the
precision needed for the application.
Next, the satellite positions are checked to ensure for this time
range the satellite positions are computed using a single set of
ephemerides to avoid discontinuities in step 731. This step 731 is
used as a check to ensure the positions are correct by using the
ephemerides as another way to calculate the satellite's
location.
Next, the corrected unambiguous high rate phase is used to
calculate the high rate receiver position during this 50-100
seconds window in step 733. This step 733 is the same as step 719
but uses the high rate corrected phase data instead of the
decimated pseudorange data.
Next, the high rate phase-based navigation solution is produced in
step 735. The high rate phase-based navigation solution indicated
where the receiver is at every 10 ms in the window.
Next, for each PRN, the high rate navigation solution is used to
calculate the distance between the receiver and the satellite at
each time in step 737.
Next, the distance between the receiver and the satellite at
t.sub.0 is subtracted from the rest, leaving the change in distance
versus time in step 739. This step 739 is optional depending on the
application; for example, for calculating only the change in the
distance, calculating the absolute distance is not needed. In an
embodiment, t.sub.0 refers to the first point (and distance)
between the receiver and the satellite. In another embodiment
t.sub.0 may refer to a reference point or distance may refer to a
defined reference distance.
Next, the change in distance is converted from meters to cycles by
dividing by the wavelength in step 741. For example, the wavelength
is approximately 20 cm for GPS L.sub.1 frequency at 1.57542 GHz.
Similarly, GPS L.sub.2 wavelength may also be used for the
corresponding signal.
Next, the change in distance between the receiver and the satellite
from the phase measurements is subtracted in step 743. In this step
743, the local motion of the monitoring device is thus removed or
reduced through the subtracted change in the distance between the
receiver and the satellite because the change in the distance
should only include satellite motion if the monitoring device is
stationary.
Next, the motion-corrected phase is used to calculate the
.sigma..sub..PHI. as described in .sigma..sub..PHI. calculation
process 600 in step 745.
Next, the motion-corrected .sigma..sub..PHI. for each
cycle-slip-free PRN for this window is produced in step 747.
FIG. 8 illustrates an exemplary flow diagram of a motion-corrected
.sigma..sub..PHI. calculation process for a monitoring device
according to an embodiment.
The .sigma..sub..PHI. calculation process 800 is similar to the
.sigma..sub..PHI. calculation process 700 as discussed above with
respect to FIG. 7. In particular, a different between
.sigma..sub..PHI. calculation process 700 and .sigma..sub..PHI.
calculation process 800 is the elimination of steps 715 to 723 from
the .sigma..sub..PHI. calculation process 700. For the specific
application of calculating .sigma..sub..PHI., it is recognized that
a navigation solution that includes absolute receiver location is
not required (e.g., the approximate receiver location as calculated
in step 719 need not be known) because the desired result is the
change in the distance between the receiver and the satellite. As
such, the calculation in steps 715 to 723 may be eliminated in
order to save processing time and power. In particular, step 723 is
generally performed using a large matrix inversion and may need
PRNs from at least five satellites. In an embodiment, if drift of
the monitoring device occurs within the 50-100 s window (e.g., the
monitoring device has lateral movement, such as moved by waves in
the ocean, that changes the absolute location of the monitoring
device), the calculated .sigma..sub..PHI. may be passed through a
high pass filter in order to filter out the drift.
The following settings for the processing algorithm performed by
the DSP 230 is recognized as preferable for computing the
motion-corrected .sigma..sub..PHI. in an empirical study as will be
discussed with respect to FIGS. 12A-12E: EML chip spacing of 0.1;
PLL bandwidth of 40 Hz, and DLL bandwidth of 0.05 Hz.
Motion-corrected .sigma..sub..PHI. calculation process 800 starts
with step 811 to read a 50-100 second window of high rate phase and
low rate (or high rate if available) pseudorange, and status flag.
Generally, scintillation may be calculated using windows of around
1 minute, hence the 50-100 second window.
Next, the phase, pseudorange, and status flag are interpolated onto
a common high rate timestamp in step 813. The interpolation may be
done using interpolation methods as known now or may be later
derived (e.g., linear or quadratic interpolation). As every PRN has
its own time series but with an offset of a certain time (e.g., on
the order of ms), the interpolation obtains further resolution of
the data on an integrated carrier phase. In an embodiment, a linear
interpolation may be computed at around 100 Hz, and quadratic
interpolation may be computed at around 25 Hz.
Next, PRN that is not continuous for the entire time range is
filtered out in step 815. In an embodiment, the corresponding
validity and cycle slip flags of the data are used to filter out
the non-continuous PRNs. For example, the non-continuous PRN as
illustrated in FIG. 11B may include a corresponding validity flag
and non-cycle slip free PRN as illustrated in FIG. 11C may include
a corresponding cycle slip flag.
Next, the average offset between the pseudorange and phase for each
PRN is calculated 816. In an embodiment, the offset may be the
average difference between the phase and the pseudorange for a
window. Next, the calculated offset is added into the high rate
phase for each PRN in step 817.
Next, the receiver location is used to add ionospheric,
tropospheric, and relativistic corrections to the unambiguous high
rate phase in step 819.
Next, the satellite positions is checked to ensure for this time
range the satellite positions are computed using a single set of
ephemerides to avoid discontinuities in step 821. This step 821 is
used as a check to ensure the positions are correct by using the
ephemerides as another way to calculate the satellite's
location.
Next, the corrected unambiguous high rate phase is used to
calculate the high rate receiver position during this 50-100
seconds window in step 823.
Next, the high rate phase-based navigation solution is produced in
step 825. The high rate phase-based navigation solution indicated
where the receiver is at every 10 ms in the window.
Next, for each PRN, high rate navigation solution is used to
calculate the distance between the receiver and the satellite at
each time in step 827.
Next, the distance between the receiver and the satellite at
t.sub.0 is subtracted from the rest, leaving the change in distance
versus time in step 829. This step 829 is optional depending on the
application; for example, for calculating only the change in the
distance, calculating the absolute distance is not needed. In an
embodiment, t.sub.0 refers to the first point (and distance)
between the receiver and the satellite.
Next, the change in distance is converted from meters to cycles by
dividing by the wavelength in step 831. For example, the wavelength
is approximately 20 cm for GPS L.sub.1 frequency at 1.58 GHz.
Similarly, GPS L.sub.2 frequency at 1227.60 GHz wavelength may also
be used for the corresponding signal.
Next, the change in distance between the receiver and the satellite
from the phase measurements is subtracted in step 833. In this step
833, the local motion of the monitoring device is thus removed or
reduced through the subtracted change in the distance between the
receiver and the satellite because the change in the distance
should only include satellite motion if the monitoring device is
stationary.
Next, the motion-corrected phase is used to calculate the
.sigma..sub..PHI. as described in .sigma..sub..PHI. calculation
process 600 in step 835. As discussed above, a high pass filter may
be used on the calculated .sigma..sub..PHI. in order to remove any
draft of the monitoring device
Next, the motion-corrected .sigma..sub..PHI. for each
cycle-slip-free PRN for this window is produced in step 837.
FIG. 9 illustrates an exemplary flow diagram of a motion-corrected
S.sub.4 process for a monitoring device according to an
embodiment.
The rocking of the antenna 290 for a monitoring device 200 deployed
at a non-fixed location, but it induces periodic C/N.sub.0
variation due at least partly to non-uniform antenna gain pattern
from rocking motion of a monitoring device 200 due to riding the
waves in the ocean, which artificially raises the measured S.sub.4
index for a monitoring device 200 deployed. An inertial measurement
unit (IMU) may be used to monitor antenna rocking, which, in
combination with the antenna gain pattern, will enable the removal
of the effect of rocking from the signal amplitude before
calculating S.sub.4.
In a preferred embodiment, an IMU may include a three-axis
accelerometer, gyroscope, and magnetometer that provide the pitch,
yaw, and roll component of the motion of the monitoring device 200.
Assuming that the measurements from the IMU are accurate, the
change in the GPS signal amplitude is a function of the tilt angle
of the antenna relative to the satellite and the gain pattern of
the respective antenna. The resulting change in the GPS signal
amplitude may then be corrected to the GPS signal amplitude so that
a more accurate S.sub.4 index may be calculated.
However, IMUs may not be relatively accurate in providing the
pitch, yaw, and roll measurements of the monitoring device 200. In
one embodiment, an array of IMU may be used and averaged for this
process to get better measurements. In another embodiment, an
alternate method may be to use data of a time-synchronized IMU so
that the characterization of the pitch, roll, and yaw of the
monitoring device 200 is in sync with the high rate phase data. An
implementation of the motion-corrected S.sub.4 process 900 is as
follows.
In an embodiment, the motion-corrected S.sub.4 process 900 may be
performed for a monitoring device 200, a support module 400, or on
a platform (e.g., a floating platform) that have motion in sync
with the monitoring device 200. The IMU 911 is placed on the
monitoring device 200, the support module 400, or the platform to
measure the respective motions of the monitoring device 200 using a
combination of one or more magnetometer, gyroscope, and
accelerometer 909 of the IMU 911. In an embodiment, the pitch and
roll components 919 of the motion may be derived by passing the
data from the gyroscope and the accelerometer through a Kalman
Filter 917. The yaw component may be derived from the magnetometer.
In an embodiment, the yaw component 915 may be derived from a
separate magnetometer that is installed on the monitoring device
200, the support module 400, or the waveglider 913 or other
platform. This may be needed due to inaccuracies in the IMU 911.
The waveglider 913 provides a float heading that translates the yaw
component 915.
The relative position 907 may be derived from the accelerometer,
e.g., calculated with a double integral. The relative position 907
is used for matching with the data from the GPS calculation. In one
embodiment, the data from GPS calculated in the motion-corrected
.sigma..sub..PHI. process 700 or motion-corrected .sigma..sub..PHI.
process 800. For example, one data from the GPS calculation that
may be useful is the satellite position 921. In an embodiment, the
raw data from the GPS 901 is used to calculate the high rate phase
navigation solution 903; this is also available from the
motion-corrected .sigma..sub..PHI. process 700 or motion-corrected
.sigma..sub..PHI. process 800. The IMU data is cross-correlated and
fitted with the high rate phase navigation solution in order to
align both data into a common time. In an embodiment, data fitting
techniques as now known or later derived may be used. In an
alternate embodiment, the cross-correlation and the fitting may be
done manually.
With a measurement of yaw 915 and pitch and roll 919, the title
angle of the antenna relative to the GPS satellite may be
determined using the calculated satellite position 921. This
calculated satellite position 921 may be determined in the
motion-corrected .sigma..sub..PHI. process 700 or motion-corrected
.sigma..sub..PHI. process 800. Using the antenna gain pattern 925,
the change in the GPS signal amplitude 927 may be determined
according to the tilt angle of the antenna relative to the GPS
satellite 923 as a function of the antenna gain pattern 925, The
S.sub.4 929 may be calculated based on difference of the gain of
the antenna without a tilt angle relative to the satellite and with
change in the GPS signal amplitude 927 due to the tilt angle. As
such, the motion corrected S.sub.4 931 may be calculated.
FIG. 10A-10B illustrate exemplary flow diagrams of a wave height
calculation process for a monitoring device according to an
embodiment.
It is noted that the wave height calculation process 1000 uses
similar steps as the motion-corrected .sigma..sub..PHI. process 700
or motion-corrected .sigma..sub..PHI. process 800. For example, the
steps 1011 to 1033 corresponds with steps 711 to 733 of process 700
and steps 811 to 823 of process 800. As such, the calculations of
the GPS signals from the process 700 or process 800 may be reused
for the wave height calculation process 1000.
Wave height calculation process 1000 starts with step 1011 to read
a 50-100 second window of high rate phase and low rate (or high
rate if available) pseudorange, and status flag.
Next, the phase, pseudorange, and status flag are interpolated onto
a common high rate timestamp in step 1013.
Next, the corresponding validity and cycle slip flags of the data
are used to assign a unique arc number to each continuous high rate
phase arc in step 1015.
Next, an approximately one (1) second decimated copy of all data is
made in step 1017. This step 1017 may be optional because the
receiver location is not ultimately needed for the calculation as
discussed with respect to FIG. 8.
Next, the decimated pseudorange is used to calculate an approximate
receiver location in step 1019. This step 1019 may be optional
because the receiver location is not ultimately needed for the
calculation as discussed with respect to FIG. 8.
Next, the approximate receiver location is used to add ionospheric,
tropospheric, and relativistic corrections to the decimated phase
in step 1021. This step 1021 may be optional because the receiver
location is not ultimately needed for the calculation as discussed
with respect to FIG. 8.
Next, the corrected decimated phase is used to solve the phase
ambiguity for each arc in step 1023. This step 1023 may be optional
because the absolute receiver location is not ultimately needed for
the calculation as discussed with respect to FIGS. 8A-8B.
Next, any arcs that are not continuous for the entire time range
are filtered out in step 1025.
Next, the calculated ambiguity is added into the high rate phase
for each arc in step 1027.
Next, the receiver location is used to add ionospheric,
tropospheric, and relativistic corrections to the unambiguous high
rate phase in step 1029.
Next, the satellite positions are checked to ensure for this time
range the satellite positions are computed using a single set of
ephemerides to avoid discontinuities in step 1031.
Next, the corrected unambiguous high rate phase is used to
calculate high rate receiver position during this about 50 seconds
to about 100 seconds window in step 1033. As discussed with respect
to FIGS. 8A-8B, the high rate receiver position calculated in this
step 1033 may contain a drift of the monitoring device 200
unaccounted for. This drift can be removed using a high pass
filter, which will be discussed with respect to steps 1035 and
1037.
Next, the antenna height is detrended to remove low frequency
motion in step 1035. In an embodiment, the coordinates of the
receiver position (as calculated in step 1033) may be transferred
as a height of the antenna, e.g., by calculating Euclidean
distance. The low frequency motion is the difference between the
known length of the GPS antenna and the calculated height of the
antenna from the receiver position. In an embodiment, a high pass
filter may be used to remove any low frequency component of the
motion, which may be an indication of drifting of the monitoring
device 200 rather than the cyclical motion of a wave. In an
embodiment, the high frequency component may be defined as the
motion component with a period greater than 30 seconds.
Next, the high frequency (less than about a 30 second period)
antenna/wave height is produced in step 1037.
In an embodiment, the wave height calculation process 1000 may be
used for other applications such as tsunami detection and warning.
For example, a number of monitoring devices 200 may be deployed at
various locations tracking the wave height at each location. A
number of monitoring devices 200 at a region or near a coastal area
that is tracking abnormally high wave height may indicate a tsunami
at the region or near the coastal area. In a further embodiment,
the data may be aggregated by a server as packaged data as
discussed with respect to steps 543 and 544 in FIG. 5C.
FIGS. 11A-11C illustrate exemplary PRNs according to an
embodiment.
Referring the FIG. 11A, the PRN 13 contains an arc 1 that is
continuous over the range of the 100 s window. Referring to FIG.
11B, the PRN 17 contains an invalid arc 2 that contains data for
less than 20 s. Referring to FIG. 11C, the PRN 20 contains an arc 3
from 0 s to around 90 s, a slip at around 90 s, and an arc 4 from
around 90 s to 100 s.
FIGS. 12A-12E illustrate .sigma..sub..PHI. measurements and
calculations for a test of a monitoring device according to an
embodiment.
The approximately 32 hour ocean test was conducted on off the coast
of Hawaii. A GPS data acquisition system was deployed to record the
raw GPS L.sub.1 spectrum from the ocean using the Liquid Robotics
Wave Glider SV2 platform. The raw data acquisition system consisted
of a GPS RFE board which downconverts the GPS L.sub.1 spectrum to
an intermediate frequency, and then samples it at 5.7 MHz. This
data was read by an embedded Linux computer connected to a USB
acquisition board, and then saved to a local hard drive for
post-processing. An IMU was also installed on the platform to
record 50 Hz 3-axis accelerometer, gyro, and magnetometer data to
study the wave motion itself during the test.
This raw GPS data set was post-processed to acquire and track the
GPS signals present in the recorded spectrum. Different
combinations of EML spacing, PLL loop order, PLL bandwidth, and DLL
bandwidth were tested to study the effect of each parameter on GPS
tracking performance, measurement accuracy, and noise level from
this mobile platform. These same combinations of parameters were
also tested on data from a stationary antenna in Boulder, Colo. to
investigate their effect on measurement accuracy and noise level
for a stationary reference station.
The result of this analysis is a highly optimized set of GPS
tracking parameters for an ocean-going vehicle to significantly
improve GPS tracking performance with minimal impact on data
quality. Once the optimal settings were determined, that data set
was used as the baseline for testing several antenna motion removal
algorithms for improving .sigma..sub..PHI. and S.sub.4 calculations
on a moving platform.
FIG. 12A shows the .sigma..sub..PHI. from the buoy without motion
correction. FIG. 12B shows the .sigma..sub..PHI. from the buoy with
motion correction.
FIG. 12C shows an enlarged view of the .sigma..sub..PHI. from the
buoy with motion correction as shown in FIG. 12B. This is compared
with the .sigma..sub..PHI. from the ground station shown in FIG.
12D and the MKEA ROTI index shown in FIG. 12E.
Example
Without intending to limit the scope of the invention, the
following example illustrates how various embodiments of the
invention may be made and/or used.
This Example illustrates the deployment of a monitoring device in
an oceanic environment and the calculating of the ionospheric
scintillation and the wave height.
In this Example, the experimental setup included a monitoring
device mounted on a liquid robotics wave glider SV2 platform. The
monitoring device was configured to record raw GPS L.sub.1
spectrums. The monitoring device included an antenna, radio
frequency front end (RFE) hardware, USB digital acquisition board,
embedded Linux computer, and storage device.
The antenna was an Antcom 53G1215A-XT-1 dual frequency active GPS
patch antenna for receiving a radio signal from a number of GPS
satellites.
The radio frequency front end (RFE) hardware was configured to down
convert the GPS L.sub.1 spectrum to an intermediate frequency of
1.610476 MHz. The GPS RF front end board was the custom front end
board used in ASTRA'S SM-211 Dual Frequency Software GPS receiver.
The data sheet describing the SM-211 receiver is hereby
incorporated herein by reference.
The USB digital acquisition board was configured to read the serial
data stream from the RFE board and send it over USB to the Linux
computer. The USB digital acquisition board was an ACCES I/O
USB-DI16A.
The embedded Linux computer was configured to read the digital data
stream from the USB digital acquisition board, as well as the
digital data stream from the IMU, and write both data sets to a
local storage device. The embedded Linux computer was a fit-PC2i 2
GB/2 GHz model with Linux Mint installed.
The storage device was configured to record the raw data from the
USB digital acquisition board and the IMU. The storage device was
an Intel SSDSA2CW600G3B5 600 GB solid state drive.
An IMU was also utilized. The IMU was configured to record 50 Hz
three-axis accelerometer, gyro, and magnetometer data to study the
wave motion itself during this example. The IMU was a CH Robotics
UM6 orientation sensor.
The monitoring system and IMU were installed/affixed to the Liquid
Robotics Wave Glider SV2 is an unmanned autonomous marine robot to
use only the ocean's endless supply of wave energy for propulsion.
It is described with reference to U.S. Pat. No. 7,371,136, which is
hereby incorporated by reference. It employed the monitoring system
mounted in the forward payload compartment inside a sealed dry box
to protect it from the ocean.
Example Method
Step 1: A 32 hour ocean test was conducted in Hawaii from 17:50 UTC
on the first day to 1:30 UTC on the third day and data was
obtained. The data included the raw GPS L.sub.1 spectrum during
that time range, including data from all 32 GPS satellites, e.g.,
PRN1-PRN32.
Step 2: This raw spectrum was post-processed in order to acquire
and track the signals from any and all GPS satellites contained
within. This process includes the calculation of all typical GNSS
observables, including 100 Hz integrated carrier phase, in-phase
accumulation, quadrature accumulation, GPS time, and receiver time,
as well as 1 Hz pseudorange, integrated carrier phase, GPS time,
receiver time, Doppler frequency, SV elevation, SV azimuth, C/NO,
data validity flag, cycle slip flag, signal acquisition status,
PRN, SV health, and 0.01 Hz S.sub.4, .sigma..sub..PHI.,
.tau..sub.0, scintillation power ratio, GPS time, reference channel
status, and PRN for each satellite being tracked, as well as 1 Hz
receiver X/Y/Z position, receiver X/Y/Z GPS time, receiver time,
velocity, receiver clock error, receiver clock error rate, and
navigation solution flag. Over the course of the test, all 32 GPS
satellites were acquired and tracked.
Referring to FIG. 12A, the calculated .sigma..sub..PHI. index for
the entire time range is shown. Note that this is the standard
.sigma..sub..PHI. index with no antenna motion correction. Each PRN
is in a different color to uniquely identify them.
Step 3: The 32 hour time range was subdivided into approximately
1140 individual 100 second chucks for scintillation
calculation.
Step 4: For each 100 second window, the 100 Hz phase and 1 Hz
pseudorange and status flags for each GPS PRN in view was
found.
Referring to FIG. 11A, 100 seconds of 100 Hz phase data collected
from GPS PRN 13 is shown.
Referring to FIG. 11B, 100 seconds of 100 Hz phase data collected
from GPS PRN 17 is shown.
Referring to FIG. 11C, 100 seconds of 100 Hz phase data collected
from GPS PRN 20 is shown.
Step 5: For each 100 second window, the 100 Hz phase data from each
PRN in view was linearly interpolated onto a common 100 Hz time
scale.
Step 6: For each 100 second window and each PRN, the validity and
cycle slip flags were used to divide the high rate phase time
series into continuous cycle-slip free arcs.
Step 7: For each 100 second window, the 1 Hz pseudorange data was
used to calculate an approximate receiver location.
Step 8: For each 100 second window and each PRN, the approximate
receiver location was used to add ionospheric, tropospheric, and
relativistic corrections to the 1 Hz phase data.
Step 9: For each 100 second window, the corrected 1 Hz phase data
was used solve for the ambiguity in each continuous phase arc,
according to the process disclosed in Joseph M. Strus, et al.,
"Precise Point Positioning Method for a Static Survey in a High
Multipath Environment," ION GNSS 17th International Technical
Meeting of the Satellite Division, 21-24 Sep. 2004, p. 1856-63,
under the section entitled "Multiple Epoch TOA", which is hereby
incorporated by reference in its entirety.
Step 10: For each 100 second window, any arcs that were not
continuous over the entire time range were filtered out, as they
would corrupt the high rate navigation solution and prevent the
accurate removal of antenna motion for all other PRNs.
Step 11: For each 100 second window and each PRN, the calculated
ambiguity was added to the 100 Hz phase data.
Step 12: For each 100 second window and each PRN, the approximate
receiver location was used to add ionospheric, tropospheric, and
relativistic corrections to the 100 Hz phase data.
Step 13: For each 100 second window, the satellite positions were
computed at 100 Hz using a static set of ephemerides, to prevent an
ephemerides update from introducing a discontinuity in the
resulting navigation solution.
Step 14: For each 100 second window, the 100 Hz phase data from
each PRN was used to calculate the receiver position at 100 Hz.
Step 15: For each 100 second window and each PRN, the 100 Hz
receiver position and 100 Hz satellite position information were
used to calculate the 100 Hz distance between the receiver and the
satellite.
Step 16: For each 100 second window and each PRN, the distance
between the receiver and the satellite was converted from meters to
cycles by dividing by the GPS L.sub.1 wavelength of 0.19029367
meters/cycle.
Step 17: For each 100 second window and each PRN, the distance
between the receiver and the satellite was subtracted from the 100
Hz phase data, in order to remove the effects of receiver and
satellite motion from the data.
Step 18: For each 100 second window and each PRN, the 100 Hz phase
data was used to calculate .sigma..sub..PHI. in the normal fashion,
including the subtraction of a reference satellite to compensate
for local receiver clock errors.
Referring to FIG. 12B, the resulting .sigma..sub..PHI. index for
the entire time range is shown, this time including antenna motion
correction. Each PRN is in a different color to uniquely identify
them. This figure is shown on the same scale as FIG. 12A to
highlight the amplitude of the antenna motion correction.
Referring to FIG. 12C, the resulting .sigma..sub..PHI. index for a
limited time range of about 10 hours is shown. This makes clear a
small increase in the .sigma..sub..PHI. index for PRN 6 at
approximately 15 UT on the second day, shown in blue.
Referring to FIG. 12D, the .sigma..sub..PHI. index for a nearby
CASES SM-211 receiver located on the shore nearby is shown, which
identifies a similar increase in the .sigma..sub..PHI. index on PRN
6 at the same time.
Referring to FIG. 12E, the ROTI index for a nearby CORS receiver
located on Mauna Kea is shown, which identifies a similar increase
in the ROTI index on PRN 6 at the same time.
The result of this Example illustrate that the motion correction
algorithm undertaken to correct the .sigma..sub..PHI. index was
highly effective at reducing the effect of antenna motion on this
ocean-going platform, referring to the difference between FIG. 12A
and FIG. 12B. This Example also illustrates that the resulting
.sigma..sub..PHI. index is still sensitive enough to detect the
small level of ionospheric variability seen in PRN 6 at around 15
UT on the second day, referring to FIG. 12C, FIG. 12D, and FIG.
12E.
Also, while the flowcharts have been discussed and illustrated in
relation to a particular sequence of events, it should be
appreciated that changes, additions, and omissions to this sequence
can occur without materially affecting the operation of the
disclosed embodiments, configuration, and aspects.
A number of variations and modifications of the disclosure can be
used. It would be possible to provide for some features of the
disclosure without providing others.
In yet another embodiment, the systems and methods of this
disclosure can be implemented in conjunction with a special purpose
computer, a programmed microprocessor or microcontroller and
peripheral integrated circuit element(s), an ASIC or other
integrated circuit, a digital signal processor, a hard-wired
electronic or logic circuit such as a discrete element circuit, a
programmable logic device or gate array such as PLD, PLA, FPGA,
PAL, special purpose computer, any comparable means, or the like.
In general, any device(s) or means capable of implementing the
methodology illustrated herein can be used to implement the various
aspects of this disclosure. Exemplary hardware that can be used for
the disclosed embodiments, configurations and aspects includes
computers, handheld devices, telephones (e.g., cellular, Internet
enabled, digital, analog, hybrids, and others), and other hardware
known in the art. Some of these devices include processors (e.g., a
single or multiple microprocessors), memory, nonvolatile storage,
input devices, and output devices. Furthermore, alternative
software implementations including, but not limited to, distributed
processing or component/object distributed processing, parallel
processing, or virtual machine processing can also be constructed
to implement the methods described herein.
In yet another embodiment, the disclosed methods may be readily
implemented in conjunction with software using object or
object-oriented software development environments that provide
portable source code that can be used on a variety of computer or
workstation platforms. Alternatively, the disclosed system may be
implemented partially or fully in hardware using standard logic
circuits or VLSI design. Whether software or hardware is used to
implement the systems in accordance with this disclosure is
dependent on the speed and/or efficiency requirements of the
system, the particular function, and the particular software or
hardware systems or microprocessor or microcomputer systems being
utilized.
In yet another embodiment, the disclosed methods may be partially
implemented in software that can be stored on a storage medium,
executed on programmed general-purpose computer with the
cooperation of a controller and memory, a special purpose computer,
a microprocessor, or the like. In these instances, the systems and
methods of this disclosure can be implemented as a program embedded
on personal computer such as an applet, JAVA.RTM. or CGI script, as
a resource residing on a server or computer workstation, as a
routine embedded in a dedicated measurement system, system
component, or the like. The system can also be implemented by
physically incorporating the system and/or method into a software
and/or hardware system.
Although the present disclosure describes components and functions
implemented in the aspects, embodiments, and/or configurations with
reference to particular standards and protocols, the aspects,
embodiments, and/or configurations are not limited to such
standards and protocols. Other similar standards and protocols not
mentioned herein are in existence and are considered to be included
in the present disclosure. Moreover, the standards and protocols
mentioned herein and other similar standards and protocols not
mentioned herein are periodically superseded by faster or more
effective equivalents having essentially the same functions. Such
replacement standards and protocols having the same functions are
considered equivalents included in the present disclosure.
The present disclosure, in various aspects, embodiments, and/or
configurations, includes components, methods, processes, systems
and/or apparatus substantially as depicted and described herein,
including various aspects, embodiments, configurations embodiments,
subcombinations, and/or subsets thereof. Those of skill in the art
will understand how to make and use the disclosed aspects,
embodiments, and/or configurations after understanding the present
disclosure. The present disclosure, in various aspects,
embodiments, and/or configurations, includes providing devices and
processes in the absence of items not depicted and/or described
herein or in various aspects, embodiments, and/or configurations
hereof, including in the absence of such items as may have been
used in previous devices or processes, e.g., for improving
performance, achieving ease and/or reducing cost of
implementation.
The foregoing discussion has been presented for purposes of
illustration and description. The foregoing is not intended to
limit the disclosure to the form or forms disclosed herein. In the
foregoing description for example, various features of the
disclosure are grouped together in one or more aspects,
embodiments, and/or configurations for the purpose of streamlining
the disclosure. The features of the aspects, embodiments, and/or
configurations of the disclosure may be combined in alternate
aspects, embodiments, and/or configurations other than those
discussed above. This method of disclosure is not to be interpreted
as reflecting an intention that the claims require more features
than are expressly recited in each claim. Rather, as the following
claims reflect, inventive aspects lie in less than all features of
a single foregoing disclosed aspect, embodiment, and/or
configuration. Thus, the following claims are hereby incorporated
into this description, with each claim standing on its own as a
separate preferred embodiment of the disclosure.
Moreover, though the description has included a description of one
or more aspects, embodiments, and/or configurations and certain
variations and modifications, other variations, combinations, and
modifications are within the scope of the disclosure, e.g., as may
be within the skill and knowledge of those in the art, after
understanding the present disclosure. It is intended to obtain
rights which include alternative aspects, embodiments, and/or
configurations to the extent permitted, including alternate,
interchangeable and/or equivalent structures, functions, ranges or
steps to those claimed, whether or not such alternate,
interchangeable and/or equivalent structures, functions, ranges or
steps are disclosed herein, and without intending to publicly
dedicate any patentable subject matter.
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